Zequn Jie

5.9k total citations · 1 hit paper
47 papers, 2.0k citations indexed

About

Zequn Jie is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Zequn Jie has authored 47 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 3 papers in Computational Mechanics. Recurrent topics in Zequn Jie's work include Advanced Neural Network Applications (21 papers), Advanced Image and Video Retrieval Techniques (20 papers) and Multimodal Machine Learning Applications (15 papers). Zequn Jie is often cited by papers focused on Advanced Neural Network Applications (21 papers), Advanced Image and Video Retrieval Techniques (20 papers) and Multimodal Machine Learning Applications (15 papers). Zequn Jie collaborates with scholars based in China, Singapore and United States. Zequn Jie's co-authors include Jiashi Feng, Wei Liu, Lin Ma, Shuicheng Yan, Li Shen, Fangyu Zou, Weizhong Zhang, Jingyuan Chen, Xin Huang and Xinpeng Chen and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Zequn Jie

46 papers receiving 2.0k citations

Hit Papers

A Sufficient Condition for Convergences of Adam and RMSProp 2019 2026 2021 2023 2019 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Sufficient Condition for Convergences of Adam and RMSProp
    2019 264 citations Fangyu Zou, Li Shen et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zequn Jie China 20 1.6k 563 132 107 100 47 2.0k
Jeongmin Park South Korea 20 694 0.4× 472 0.8× 141 1.1× 84 0.8× 67 0.7× 105 1.4k
Yuwei Wu China 24 1.2k 0.8× 619 1.1× 94 0.7× 70 0.7× 275 2.8× 83 1.7k
Siyuan Qiao United States 13 1.0k 0.6× 375 0.7× 70 0.5× 185 1.7× 167 1.7× 25 1.4k
Xiaoheng Jiang China 16 847 0.5× 517 0.9× 72 0.5× 64 0.6× 114 1.1× 52 1.4k
Yazhou Yao China 25 1.5k 0.9× 1.0k 1.8× 66 0.5× 92 0.9× 255 2.5× 96 2.0k
Henghui Ding Singapore 29 1.8k 1.1× 922 1.6× 109 0.8× 100 0.9× 147 1.5× 78 2.3k
Joanna Materzyńska Mexico 6 2.0k 1.2× 1.1k 1.9× 215 1.6× 182 1.7× 88 0.9× 6 2.3k
Doyen Sahoo Singapore 11 607 0.4× 428 0.8× 64 0.5× 100 0.9× 105 1.1× 21 1.3k
Xuequan Lu Australia 23 924 0.6× 540 1.0× 83 0.6× 61 0.6× 102 1.0× 125 1.7k
Qi She Hong Kong 15 779 0.5× 458 0.8× 116 0.9× 148 1.4× 118 1.2× 33 1.3k

Countries citing papers authored by Zequn Jie

Since Specialization
Citations

This map shows the geographic impact of Zequn Jie's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zequn Jie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zequn Jie more than expected).

Fields of papers citing papers by Zequn Jie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zequn Jie. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zequn Jie. The network helps show where Zequn Jie may publish in the future.

Co-authorship network of co-authors of Zequn Jie

This figure shows the co-authorship network connecting the top 25 collaborators of Zequn Jie. A scholar is included among the top collaborators of Zequn Jie based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zequn Jie. Zequn Jie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yuan, Yitian, et al.. (2025). Weakly-Supervised 3D Visual Grounding Based on Visual Language Alignment. IEEE Transactions on Multimedia. 27. 7662–7674.
2.
Ma, Jie, et al.. (2024). AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement Learning. 3205–3215. 10 indexed citations
3.
Wang, Tao, Xiaopeng Zhang, Francis E. H. Tay, et al.. (2023). Learnable Central Similarity Quantization for Efficient Image and Video Retrieval. IEEE Transactions on Neural Networks and Learning Systems. 35(12). 18717–18730. 8 indexed citations
4.
Lan, Xiaohan, Yitian Yuan, Hong Chen, et al.. (2023). Curriculum Multi-Negative Augmentation for Debiased Video Grounding. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 1213–1221. 10 indexed citations
5.
Shen, Li, et al.. (2023). A Unified Analysis of AdaGrad With Weighted Aggregation and Momentum Acceleration. IEEE Transactions on Neural Networks and Learning Systems. 35(10). 14482–14490. 14 indexed citations
6.
Li, Jinlong, Zequn Jie, Xu Wang, et al.. (2022). Weakly Supervised Semantic Segmentation Via Progressive Patch Learning. IEEE Transactions on Multimedia. 25. 1686–1699. 17 indexed citations
7.
Zhang, Xu‐Jie, Sha Yu, Michael Kampffmeyer, et al.. (2022). ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design. Proceedings of the 30th ACM International Conference on Multimedia. 4525–4535. 11 indexed citations
8.
Gao, Yuan, et al.. (2020). MTL-NAS: Task-Agnostic Neural Architecture Search Towards General-Purpose Multi-Task Learning. 11540–11549. 42 indexed citations
9.
Huang, Xin, Zheng Ge, Zequn Jie, & Osamu Yoshie. (2020). NMS by Representative Region: Towards Crowded Pedestrian Detection by Proposal Pairing. 10747–10756. 126 indexed citations
10.
Wang, Tao, Xiaopeng Zhang, Francis EH Tay, et al.. (2020). Central Similarity Quantization for Efficient Image and Video Retrieval. 3080–3089. 227 indexed citations
11.
12.
Zhang, Zhenyu, Zhen Cui, Chunyan Xu, et al.. (2019). Joint Task-Recursive Learning for RGB-D Scene Understanding. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(10). 2608–2623. 17 indexed citations
13.
Li, Chengzheng, Chunyan Xu, Zhen Cui, et al.. (2019). Learning Object-Wise Semantic Representation for Detection in Remote Sensing Imagery. Computer Vision and Pattern Recognition. 20–27. 18 indexed citations
14.
Li, Yuan, Tao Wang, Xiaopeng Zhang, et al.. (2019). Central Similarity Hashing via Hadamard matrix.. arXiv (Cornell University). 2 indexed citations
15.
Ma, Lin, Wenhao Jiang, Zequn Jie, & Xu Wang. (2019). Bidirectional image-sentence retrieval by local and global deep matching. Neurocomputing. 345. 36–44. 23 indexed citations
16.
Kang, Bingyi, Zequn Jie, & Jiashi Feng. (2018). Policy Optimization with Demonstrations. International Conference on Machine Learning. 2469–2478. 37 indexed citations
17.
Jin, Xiaojie, Huaxin Xiao, Xiaohui Shen, et al.. (2017). Predicting Scene Parsing and Motion Dynamics in the Future. Neural Information Processing Systems. 30. 6915–6924. 18 indexed citations
18.
Li, Xin, Zequn Jie, Wei Wang, et al.. (2017). FoveaNet: Perspective-Aware Urban Scene Parsing. 784–792. 29 indexed citations
19.
Jin, Xiaojie, Xin Li, Huaxin Xiao, et al.. (2017). Video Scene Parsing with Predictive Feature Learning. 72 indexed citations
20.
Jin, Xiaojie, Yunpeng Chen, Jiashi Feng, Zequn Jie, & Shuicheng Yan. (2016). Multi-Path Feedback Recurrent Neural Network for Scene Parsing. National Conference on Artificial Intelligence. 4096–4102. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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